Active sparse Bayesian committee machine potential for isothermal–isobaric molecular dynamics simulations
Soohaeng Yoo Willow, Dong Geon Kim, R. Sundheep, Amir Hajibabaei, Kwang S. Kim, Chang Woo Myung
Abstract
Introducing active sparse Bayesian committee machine potentials with virial kernels for enhanced pressure accuracy. This enables efficient on-the-fly training for accurate isobaric machine learning molecular dynamics simulations with reduced costs.
Topics & Concepts
Molecular dynamicsBayesian probabilityIsobaric processMachine learningKernel (algebra)Computer scienceBayesian inferenceStatistical physicsArtificial intelligencePhysicsChemistryComputational chemistryMathematicsThermodynamicsCombinatoricsMachine Learning in Materials ScienceProtein Structure and DynamicsMass Spectrometry Techniques and Applications